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Related papers: Code Llama: Open Foundation Models for Code

200 papers

Code generation by Llama 3.1 models, such as Meta's Llama 3.1 405B, represents a significant advancement in the field of artificial intelligence, particularly in natural language processing and programming automation. This paper explores…

Computation and Language · Computer Science 2025-04-03 Aniket Deroy , Subhankar Maity

Large language models (LLMs) pretrained on vast source code have achieved prominent progress in code intelligence. However, existing code LLMs have two main limitations in terms of architecture and pretraining tasks. First, they often adopt…

Computation and Language · Computer Science 2023-05-23 Yue Wang , Hung Le , Akhilesh Deepak Gotmare , Nghi D. Q. Bui , Junnan Li , Steven C. H. Hoi

Recent advancements in large language models (LLMs) like ChatGPT and LLaMA show promise in medical applications, yet challenges remain in medical language comprehension. This study presents Me-LLaMA, a new medical LLM family based on…

The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into…

Large language models (LLMs) have shown remarkable success across many domains, yet their integration into cybersecurity applications remains limited due to a lack of general-purpose cybersecurity data, representational complexity, and…

In recent years, large language models (LLMs) have emerged as powerful tools with potential applications in various fields, including software engineering. Within the scope of this research, we evaluate five different state-of-the-art LLMs…

Computation and Language · Computer Science 2024-09-09 Luis Mayer , Christian Heumann , Matthias Aßenmacher

Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning capacities, the resulting models are either closed-source…

Background: Log messages provide valuable information about the status of software systems. This information is provided in an unstructured fashion and automated approaches are applied to extract relevant parameters. To ease this process,…

Software Engineering · Computer Science 2024-09-05 Merve Astekin , Max Hort , Leon Moonen

We release and introduce the TigerBot family of large language models (LLMs), consisting of base and chat models, sized from 7, 13, 70 and 180 billion parameters. We develop our models embarking from Llama-2 and BLOOM, and push the boundary…

Computation and Language · Computer Science 2023-12-18 Ye Chen , Wei Cai , Liangmin Wu , Xiaowei Li , Zhanxuan Xin , Cong Fu

Large language models (LLMs) demonstrate strong code generation abilities in general-purpose programming languages but remain limited in specialized domains such as low-level embedded systems programming. This domain involves hardware…

Machine Learning · Computer Science 2026-03-16 Amit Singh , Vedant Nipane , Pulkit Agrawal , Jatin Kishnani , Sairanjan Mishra

Code Large Language Models (Code LLMs) have gained significant attention in the industry due to their wide applications in the full lifecycle of software engineering. However, the effectiveness of existing models in understanding…

Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks, yet the majority of high-performing models remain closed-source or partially open, limiting transparency and reproducibility. In this work,…

Large Language Models (LLMs) have transformed software development by enabling code generation, automated debugging, and complex reasoning. However, their continued advancement is constrained by the scarcity of high-quality, publicly…

Software Engineering · Computer Science 2025-08-11 Wasi Uddin Ahmad , Aleksander Ficek , Mehrzad Samadi , Jocelyn Huang , Vahid Noroozi , Somshubra Majumdar , Boris Ginsburg

Decompilation aims to convert binary code to high-level source code, but traditional tools like Ghidra often produce results that are difficult to read and execute. Motivated by the advancements in Large Language Models (LLMs), we propose…

Programming Languages · Computer Science 2025-08-06 Hanzhuo Tan , Qi Luo , Jing Li , Yuqun Zhang

Code reviews are an integral part of software development and have been recognized as a crucial practice for minimizing bugs and favouring higher code quality. They serve as an important checkpoint before committing code and play an…

Software Engineering · Computer Science 2024-12-05 Genevieve Caumartin , Qiaolin Qin , Sharon Chatragadda , Janmitsinh Panjrolia , Heng Li , Diego Elias Costa

Recent development of large language models (LLMs) for code like CodeX and CodeT5+ demonstrates tremendous promise in achieving code intelligence. Their ability of synthesizing code that completes a program for performing a pre-defined task…

Computation and Language · Computer Science 2023-10-10 Weimin Xiong , Yiwen Guo , Hao Chen

Large Language Models (LLMs) have garnered remarkable advancements across diverse code-related tasks, known as Code LLMs, particularly in code generation that generates source code with LLM from natural language descriptions. This…

Computation and Language · Computer Science 2025-10-28 Juyong Jiang , Fan Wang , Jiasi Shen , Sungju Kim , Sunghun Kim

Large Language Models (LLMs) are widely adopted for assisting in software development tasks, yet their performance evaluations have narrowly focused on the functional correctness of generated code. Human programmers, however, require…

Software Engineering · Computer Science 2024-12-06 Yun Peng , Akhilesh Deepak Gotmare , Michael Lyu , Caiming Xiong , Silvio Savarese , Doyen Sahoo

Although powerful, current cutting-edge LLMs may not fulfil the needs of highly specialised sectors. We introduce KodeXv0.1, a family of large language models that outclass GPT-4 in financial question answering. We utilise the base variants…

Computation and Language · Computer Science 2024-09-24 Neel Rajani , Lilli Kiessling , Aleksandr Ogaltsov , Claus Lang